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AI Beats Four Top Poker Players

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Re: AI Beats Four Top Poker Players

#201
post #199

Earlier quoted context omitted.

>there is always a "correct" answer That's wrong. Even when you're holding a good hand, your opponent could hold a better one and reading them is a key element of poker. The opponent's hand is an important variable to decide whether you hold the winning hand or not. If you look at the experiment in detail, you'll find that it was set up in the AI's favor. >When a hand was all-in before the river no more cards were de…

>>If you look at the experiment in detail, you'll find that it was set up in the AI's favor. Could you elaborate on this ?

Links were posted here: https://news.ycombinator.com/item?id=13535714

As expected, the AI is good at making technically correct decisions and "draining money" from a table by playing hands with sufficient data almost perfectly.

However, in decisive all-in situations with little information available, it supposedly wouldn't do so well, regardless of all the learning, but that's what it often comes down to.

>Nash Equilibrium is a strategy which ensures that the player who is using it will, at the very least, not fare worse than a player using any other strategy.

How do you make this work for situations that can cost you the game in one hand, with little information available? Without observing the opponent's behavior you can't, and for the AI that means it can be forced into making bad calls by playing aggressively, unless the game mode allows for avoiding such decisions, which was the case in this test.

Re: AI Beats Four Top Poker Players

#202
post #154

Earlier quoted context omitted.

Do you mean to say that 100% random RPSAIs have a lower winrate vs humans than RPSAIs that learn and exploit human patterns? Surely a 100% random RPSAI doesn't have a poor win rate against any other RPSAI?

A 100% random RPS AI doesn't have a poor 1-on-1 win rate against any other RPS AI, but it absolutely can have a poor rate of winning tournaments , if "poor" is defined broadly enough. For a tournament that pays cash to the top 10%, most human players would consider anything in the bottom 90% to be poor, which would include a 50% win rate from a random AI. This happens because some entrants aren't 100% random, and the…

Thanks, I understand now what you're saying.

Re: AI Beats Four Top Poker Players

#203

Earlier quoted context omitted.

The usual way these games are solved is to create an "abstract" game which is tractable, find the Nash equilibrium, and map state in the real game back to the "abstract" game. In the limit, the solutions for a well designed "abstract" game will converge to that of the real game.

You are explaining how current algorithms try to find the (approximate) Nash equilibrium (and those algorithms are far from perfect; as noted in the recent DeepStack paper, current abstraction-based programs are beatable by over 3000 mbb/g, which is four times as large as simply folding each game). But my point is that even the (exact) equilibrium strategy would not necessarily be the best strategy against given non-…

Yes, you are correct on every point. Opponent modeling and exploitation is significantly more difficult than coming up with a Nash equilibrium to an abstract game.

Re: AI Beats Four Top Poker Players

#204

Earlier quoted context omitted.

Having a poker AI that plays deterministic strategies is an obviously terrible idea, for the precise reason you mention. It makes much more sense for the strategy space to be the set of probability distributions over game moves (i.e. mixed strategies). I think that the optimal mixed strategy for each hand is immune to bluffing (over many hands it will have larger expected winnings against a bluffer). If that wasn't t…

I was just making an informal remark, but reading your comment: > I think that the optimal mixed strategy for each hand is immune to bluffing (over many hands it will have larger expected winnings against a bluffer). If that wasn't the case, there would exist no Bayes-Nash equilibrium for the game, contradicting Nash's theorem. I believe that's true. I know for sure that heads up limit hold'em has been solved. That s…

Yeah I think you're right. just playing an equilibrium is suboptimal in the sense that it doesn't extract maximal value from the opponent. You want to be playing a best response to the opponent's strategy.

That's what you see online poker players do. They model their opponents (in the sense of labeling them as fun player, too tight, too loose, etc), then try to predict their hands based on their moves. Otherwise I guess they would be losing money: poker is zero sum by its nature, and the casino's cut on top of that makes it negative sum!

Re: AI Beats Four Top Poker Players

#205
post #160

Earlier quoted context omitted.

Machine learning experts are in higher supply, your anecdotal experience offers little weight. High demand creates a high supply which drives wages to zero.

Ha! That's an amusing interpretation of how supply and demand interact to find an equilibrium price/quantity point. A typical Econ 101 textbook says: higher demand --> higher price higher price --> higher supply higher supply --> lower price lower price --> higher demand In Econ 101 we pretend that cycle eventually reaches an equilibrium. In grad school we analyze the dynamics. But even if we believed your demand cau…

Yes and if you've actually paid attention you will see that a high salary signals other workers to flood the market with a lower salary thus starting the race to the bottom :)

Programmers have largely driven themselves to zero, just take a look at the workers on freelance websites and how much difficulty a native English speaking freelancer has against an army of commoditized labor.

There are still six digit earning engineers and always will be but you can't look at that as a metric for the massive commoditization that has occurred with generic programming in the past 15 years.

Re: AI Beats Four Top Poker Players

#206

Earlier quoted context omitted.

Machine learning experts are in higher supply, your anecdotal experience offers little weight. High demand creates a high supply which drives wages to zero.

For the foreseeable future, machine learning experts will be in sufficient supply for them (i) to have wages which are considerably above zero and (ii) have the ability to raise capital from people that don't think they're commodity labour (it cuts the other way too: if an oversupply of labour in a field as difficult-to-learn as ML does arise, the demand shortage causing wages to fall is almost certainly because ML t…

It's not enough to hire a machine learning expert if you are planning on building out your own capable ML operation confident in competing against the best and the brightest at Azure, Google & AWS. You'd need a team of ML experts.

On the other hand, it's easier to piggy back off the hard work of highly paid experts in this space now commoditized into 1/10th of a cent per application of an ML algorithm from Microsoft or Google or IBM.

Commoditization is going to be in full force as businesses realize they can just have a junior developer to plugin IBM Watson or Azure than hire an expensive PhD student who may know everything under the sun but cannot compete against an army of highly paid experts completely under the control of a highly collusive labor market.

Re: AI Beats Four Top Poker Players

#207

Earlier quoted context omitted.

I'm glad you posted it because it shows how little people understand their engineer's financial importance. Granted, engineers are required to create products and maintain it. You need product to sell. But at the marginal level for every dollar your sales person makes your engineer is not. You might argue but the product is generating revenues but that's not what drives a sale. A sale is a function of value derived f…

If good engineers are dime a dozen then why do they command >200k salary? I don't think you understand how much skill and practice goes into making a good programmer. Your ignorance is truly astonishing.

And for every engineer earning 200k salary in SV how many are earning less than that? I don't think you are seeing the bigger picture of the labor market instead basing it off of biased observation.

Re: AI Beats Four Top Poker Players

#208

Earlier quoted context omitted.

Machine learning experts are in higher supply, your anecdotal experience offers little weight. High demand creates a high supply which drives wages to zero.

Karpathy was offered in excess of a million out of school, I'm going to assume that you don't know what you're talking about. Silly google, they must've skipped Econ 101 since they hire tons of engineers and are doing TERRIBLY!

And how many Karpathy is there working for non-Google? Mariah Carrey made $140 million dollar record deal with Sony Music, there's boat load of money to make in the music scene!

Re: AI Beats Four Top Poker Players

#209
post #182

Earlier quoted context omitted.

Say that all you want, those guys play(ed? I'm out of the loop) in the big game, and...whoever you're thinking of, basically--didn't.

The "Big Game" which was run by Doyle Brunson, Chip Reese, etc had nothing to do with HUNL. It's mostly run hoping that some inexperienced player would drop in. It also almost always ran as a rotation of games to both bring in players who though they had an edge in "their" game and then exploit them in the other games. The Big Game and online HUNL are both technically "poker" but they are truly completely different g…

I'm fully aware--I was a poker pro for a while in a niche (HUSNGs).

The post I responded to slighted Negreanu, saying he wasn't a "top pro." He certainly is. Not a HU cash pro, of course, but a top pro? Absolutely. A match for the "best pro players?" Certainly.

The "best pro players" in a given niche wouldn't have sat in the big game, and he wouldn't have sat in their specialty. Overall he's the better poker player.

Re: AI Beats Four Top Poker Players

#210
post #182

Earlier quoted context omitted.

Say that all you want, those guys play(ed? I'm out of the loop) in the big game, and...whoever you're thinking of, basically--didn't.

Conversely, not many of the celebrity players have had much success playing online. Ivey did have some good years but even he has been struggling for the past few years. Almost all pros who have had success both online and live agree that live games a ridiculously soft compared to online games. The reason more online pros don't play live is because you have to live in Las Vegas or Macau to play a the highest stakes,…

I don't dispute any of that, I simply dispute whether or not Negreanu is a "top pro," or whether he would be a match for "the top pros."

He is a top pro. Not in HU cash. He couldn't hang with these guys at HU cash, at least not with his current skill in the discipline. But hey, poker is not that narrow of a term. It includes all kinds of disciplines, live and online, horse and stud and hold 'em, the list goes on.

Those same "top pros" who Negreanu wouldn't play HU Cash wouldn't sit in the big game with him.

Arguably bankroll management is the most important skill of a top poker professional, and that's maybe what big-game players are best at.

Also, a small caveat to all of your comment is that live games are soft compared to online games of the same limit. There is no online equivalent of the big game, or at least there wasn't when black friday hit and knocked me out of the professional poker scene.

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